For many forms of cancer, early detection is essential for a favorable prognosis. A cancerous growth must be detected at an early stage before the cancer is allowed to grow and spread. This is particularly true for colorectal and lung cancers. As a result, endoscopic techniques have been developed to examine the colon and tracheobronchial airways for the growth of precancerous and cancerous masses.
Regarding colorectal cancer, the American Cancer Society and the National Cancer Institute recommend routine screening in order to provide a means for early detection of abnormal growths. Under those guidelines over 50 million Americans should undergo annual colorectal screening. However, only a small percentage of the population undergoes colonoscopy screening each year. The underutilization of such screening exists, at least in part, because conventional colonoscopies require a patient to be sedated so that a flexible endoscope can be inserted into the patient's anus. Another problem is that conventional colonoscopies fail to provide access to the entire colon in approximately 15% of cases. Colonoscopies also expose patients to the risk of bowel perforation. Accordingly, it is understandable that patients are reluctant to undergo, or repeatedly subject themselves to, such an invasive procedure.
Consequently, virtual endoscopic techniques have been, and are continuing to be developed. Virtual endoscopy that utilizes computer reformation of radiologic cross-sectional images is a minimally invasive alternative to conventional fiberoptic endoscopy. Virtual endoscopy reduces the risk of perforation, does not require any sedation, and is considerably less expensive than the fiberoptic endoscopy method. For example, virtual colonoscopy techniques generally require bowel cleansing, gas distension of the colon, a 10-60 second helical computed tomography (CT) scan of a patient's abdomen and pelvis, and human visual analysis of multi-planar two-dimensional (2D) and three-dimensional (3D) images created from CT data.
Although virtual colonoscopy techniques provide excellent images of the colon in three-dimensions, a correct diagnosis relies upon a physician's ability to properly identify small (approximately 3-10 mm), and sometimes subtle, masses within hundreds of multiplanar two-dimensional and three-dimensional images. Such human inspection is time consuming, tedious, expensive, and under certain circumstances prone to error of interpretation. Accordingly, it would be highly beneficial to provide an automatic virtual endoscopic system and method for automatically analyzing and/or detecting abnormalities, such as abnormal growths, in a targeted structure or organ system, such as the walls of a colon or trachea.